An Energy Saving Model Predictive Control for Central Air-Conditioning System

In this paper, a model predictive control method is proposed to improve the performance on both temperature control and energy conservation for central air-conditioning system. Since the lack of consideration of the impact of cooling load can lead to a limitation on the energy saving effect, a cooling load model is proposed. Parameters in cooling load model, as well as the temperature model and energy consumption model are estimated. The optimal predictive controller is designed, and a Chance Constrained Programming method is utilized to solve the optimal problem with stochastic parameters. Through a solution algorithm based on Genetic Algorithm, the control vector which can keep optimal in most uncertain cases can be acquired. The comparative results show the effectiveness of the proposed method.